Homomorphic Encryption for Secure Ad Targeting: Balancing Privacy and Personalization in Digital Advertising

Swati Sinha

doi:10.32628/CSEIT24106178

Authors

Swati Sinha MICA, Ahmedabad, India Author

DOI:

https://doi.org/10.32628/CSEIT24106178

Keywords:

Homomorphic Encryption, Privacy-Preserving Ad Targeting, Secure Ad Platforms, Computational Overhead in Advertising, Privacy-Personalization Trade-off

Abstract

This article explores the application of homomorphic encryption (HE) in secure ad targeting, addressing the critical challenge of balancing personalized advertising with user privacy concerns in the digital advertising ecosystem. We examine the fundamentals of HE, its integration into ad targeting processes, and propose a privacy-preserving ad platform architecture. Through a comprehensive feasibility analysis and performance evaluation, we assess the technical challenges, computational overhead, and scalability issues associated with implementing HE in real-time ad serving. Our findings indicate that while HE offers strong privacy guarantees, it currently faces limitations in terms of latency and throughput compared to traditional ad targeting methods. We analyze the trade-offs between privacy protection and targeting effectiveness, highlighting the impact on ad relevance and personalization. The article also discusses future directions, including advancements in HE algorithms, integration with other privacy-enhancing technologies, and regulatory considerations. By synthesizing current research and experimental results, this work provides valuable insights into the potential of HE to revolutionize privacy-preserving ad targeting, paving the way for a more secure and privacy-conscious digital advertising future.

Downloads

Download data is not yet available.

References

A. Narayanan and V. Shmatikov, "Myths and fallacies of 'Personally Identifiable Information'," Communications of the ACM, vol. 53, no. 6, pp. 24-26, 2010. [Online]. Available: https://dl.acm.org/doi/10.1145/1743546.1743558 DOI: https://doi.org/10.1145/1743546.1743558

C. Gentry and D. Boneh, "A fully homomorphic encryption scheme," Stanford University, Stanford, CA, USA, 2009. [Online]. Available: https://crypto.stanford.edu/craig/craig-thesis.pdf

N. P. Smart and F. Vercauteren, "Fully homomorphic SIMD operations," Designs, Codes and Cryptography, vol. 71, no. 1, pp. 57-81, 2014. [Online]. Available: https://link.springer.com/article/10.1007/s10623-012-9720-4 DOI: https://doi.org/10.1007/s10623-012-9720-4

F. Boemer, Y. Lao, R. Cammarota, and C. Wierzynski, "nGraph-HE: A graph compiler for deep learning on homomorphically encrypted data," in Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019, pp. 3-13. [Online]. Available: https://dl.acm.org/doi/10.1145/3310273.3323047 DOI: https://doi.org/10.1145/3310273.3323047

A. Acar, H. Aksu, A. S. Uluagac, and M. Conti, "A Survey on Homomorphic Encryption Schemes: Theory and Implementation," ACM Computing Surveys, vol. 51, no. 4, pp. 1-35, 2018. [Online]. Available: https://dl.acm.org/doi/10.1145/3214303 DOI: https://doi.org/10.1145/3214303

F. Benhamouda, M. Joye, and B. Libert, "A new framework for privacy-preserving aggregation of time-series data," ACM Transactions on Information and System Security, vol. 18, no. 3, pp. 1-21, 2016. [Online]. Available: https://dl.acm.org/doi/10.1145/2873069 DOI: https://doi.org/10.1145/2873069

C. Aguilar-Melchor, J. Barrier, S. Guelton, A. Guinet, M.-O. Killijian, and T. Lepoint, "NFLlib: NTT-Based Fast Lattice Library," in Proceedings of the RSA Conference Cryptographers' Track, 2016, pp. 341-356. [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-319-29485-8_20 DOI: https://doi.org/10.1007/978-3-319-29485-8_20

M. Barni, G. Droandi, and R. Lazzeretti, "Privacy Protection in Biometric-Based Recognition Systems: A Marriage Between Cryptography and Signal Processing," IEEE Signal Processing Magazine, vol. 32, no. 5, pp. 66-76, 2015. [Online]. Available: https://ieeexplore.ieee.org/document/7192837 DOI: https://doi.org/10.1109/MSP.2015.2438131

P. Paillier, "Public-Key Cryptosystems Based on Composite Degree Residuosity Classes," in Advances in Cryptology — EUROCRYPT '99, 1999, pp. 223-238. [Online]. Available: https://link.springer.com/chapter/10.1007/3-540-48910-X_16 DOI: https://doi.org/10.1007/3-540-48910-X_16

J. H. Cheon, A. Kim, M. Kim, and Y. Song, "Homomorphic Encryption for Arithmetic of Approximate Numbers," in Advances in Cryptology – ASIACRYPT 2017, 2017, pp. 409-437. [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-319-70694-8_15 DOI: https://doi.org/10.1007/978-3-319-70694-8_15